train: weights=zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/pruned-aggressive_96, cfg=models_v5.0/yolov5s.yaml, data=pistols.yml, hyp=data/hyps/hyp.finetune.yaml, epochs=300, batch_size=-1, imgsz=416, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, evolve=None, bucket=, cache=None, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=yolov5_runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=0, freeze=[0], save_period=-1, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest, recipe=yolov5.transfer_learn_pruned.md, disable_ema=False, max_train_steps=-1, max_eval_steps=-1, one_shot=False, num_export_samples=0
github: skipping check (not a git repository), for updates see https://github.com/ultralytics/yolov5
fatal: not a git repository (or any of the parent directories): .git
YOLOv5 🚀 2022-6-30 torch 1.9.1+cu102 CUDA:0 (Tesla T4, 15110MiB)
hyperparameters: lr0=0.0032, lrf=0.12, momentum=0.843, weight_decay=0.00036, warmup_epochs=2.0, warmup_momentum=0.5, warmup_bias_lr=0.05, box=0.0296, cls=0.243, cls_pw=0.631, obj=0.301, obj_pw=0.911, iou_t=0.2, anchor_t=2.91, fl_gamma=0.0, hsv_h=0.0138, hsv_s=0.664, hsv_v=0.464, degrees=0.373, translate=0.245, scale=0.898, shear=0.602, perspective=0.0, flipud=0.00856, fliplr=0.5, mosaic=1.0, mixup=0.243, copy_paste=0.0
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs (RECOMMENDED)
TensorBoard: Start with 'tensorboard --logdir yolov5_runs/train', view at http://localhost:6006/
Obtaining new sparse zoo credentials token
Getting signed url for c13e55cb-dd6c-4492-a079-8986af0b65e6/model.pt
Downloading model file model.pt to /root/.cache/sparsezoo/c13e55cb-dd6c-4492-a079-8986af0b65e6/pytorch/model.pt
downloading...: 100% 14.1M/14.1M [00:00<00:00, 37.0MB/s]
Overriding model.yaml nc=80 with nc=1
from n params module arguments
0 -1 1 3520 yolov5.models.common.Focus [3, 32, 3]
1 -1 1 18560 yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 3 156928 yolov5.models.common.C3 [128, 128, 3]
5 -1 1 295424 yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 656896 yolov5.models.common.SPP [512, 512, [5, 9, 13]]
9 -1 1 1182720 yolov5.models.common.C3 [512, 512, 1, False]
10 -1 1 131584 yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 yolov5.models.common.Concat [1]
13 -1 1 361984 yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 yolov5.models.common.Concat [1]
17 -1 1 90880 yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 yolov5.models.common.Concat [1]
20 -1 1 296448 yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 yolov5.models.common.Concat [1]
23 -1 1 1182720 yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 16182 yolov5.models.yolo.Detect [1, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
overriding activations in model to Hardswish
YOLOv5s summary: 283 layers, 7063542 parameters, 7063542 gradients, 16.5 GFLOPs
Transferred 354/361 items from /root/.cache/sparsezoo/c13e55cb-dd6c-4492-a079-8986af0b65e6/pytorch/model.pt
AutoBatch: Computing optimal batch size for --imgsz 416
AutoBatch: CUDA:0 (Tesla T4) 14.76G total, 0.06G reserved, 0.05G allocated, 14.64G free
Params GFLOPs GPU_mem (GB) forward (ms) backward (ms) input output
7063542 6.961 0.201 16.78 14.15 (1, 3, 416, 416) list
7063542 13.92 0.310 17.35 15.45 (2, 3, 416, 416) list
7063542 27.85 0.581 18.58 18.79 (4, 3, 416, 416) list
7063542 55.69 1.126 19.02 26.23 (8, 3, 416, 416) list
7063542 111.4 2.223 32.87 50.45 (16, 3, 416, 416) list
AutoBatch: Using batch-size 96 for CUDA:0 13.28G/14.76G (90%)
Scaled weight_decay = 0.00054
optimizer: SGD with parameter groups 59 weight (no decay), 62 weight, 62 bias
albumentations: version 1.0.3 required by YOLOv5, but version 0.1.12 is currently installed
train: Scanning '/content/dataset/guns/train/data' images and labels...2377 found, 0 missing, 0 empty, 0 corrupt: 100% 2377/2377 [00:01<00:00, 1379.73it/s]
train: New cache created: /content/dataset/guns/train/data.cache
val: Scanning '/content/dataset/guns/val/data' images and labels...297 found, 0 missing, 0 empty, 0 corrupt: 100% 297/297 [00:00<00:00, 634.83it/s]
val: New cache created: /content/dataset/guns/val/data.cache
Plotting labels to yolov5_runs/train/exp2/labels.jpg...
AutoAnchor: 2.95 anchors/target, 1.000 Best Possible Recall (BPR). Current anchors are a good fit to dataset ✅
Image sizes 416 train, 416 val
Using 2 dataloader workers
Logging results to yolov5_runs/train/exp2
Starting training for 300 epochs...
Disabling LR scheduler, managing LR using SparseML recipe
Overriding number of epochs from SparseML manager to 50
Epoch gpu_mem box obj cls labels img_size
0/49 12.2G 0.07143 0.005311 0 243 416: 100% 25/25 [00:35<00:00, 1.43s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:04<00:00, 2.16s/it]
all 297 357 0.0179 0.185 0.0106 0.00189
Epoch gpu_mem box obj cls labels img_size
1/49 14.3G 0.0591 0.005631 0 237 416: 100% 25/25 [00:32<00:00, 1.30s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.95s/it]
all 297 357 0.11 0.199 0.0727 0.0206
Epoch gpu_mem box obj cls labels img_size
2/49 12.3G 0.0511 0.005889 0 186 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.61s/it]
all 297 357 0.356 0.401 0.275 0.0831
Epoch gpu_mem box obj cls labels img_size
3/49 12.9G 0.04455 0.006083 0 195 416: 100% 25/25 [00:33<00:00, 1.33s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.53s/it]
all 297 357 0.419 0.473 0.406 0.132
Epoch gpu_mem box obj cls labels img_size
4/49 12.9G 0.03806 0.006098 0 233 416: 100% 25/25 [00:32<00:00, 1.32s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.50s/it]
all 297 357 0.555 0.605 0.598 0.259
Epoch gpu_mem box obj cls labels img_size
5/49 12.9G 0.03427 0.005962 0 258 416: 100% 25/25 [00:32<00:00, 1.30s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.46s/it]
all 297 357 0.729 0.591 0.686 0.347
Epoch gpu_mem box obj cls labels img_size
6/49 12.9G 0.03197 0.00576 0 207 416: 100% 25/25 [00:33<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.47s/it]
all 297 357 0.718 0.669 0.718 0.392
Epoch gpu_mem box obj cls labels img_size
7/49 12.9G 0.03004 0.005625 0 254 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.52s/it]
all 297 357 0.749 0.669 0.737 0.411
Epoch gpu_mem box obj cls labels img_size
8/49 13G 0.02922 0.005537 0 235 416: 100% 25/25 [00:34<00:00, 1.38s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.44s/it]
all 297 357 0.701 0.691 0.752 0.436
Epoch gpu_mem box obj cls labels img_size
9/49 13G 0.02814 0.005131 0 196 416: 100% 25/25 [00:33<00:00, 1.35s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.47s/it]
all 297 357 0.717 0.709 0.772 0.447
Epoch gpu_mem box obj cls labels img_size
10/49 13G 0.02756 0.005152 0 247 416: 100% 25/25 [00:34<00:00, 1.37s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.48s/it]
all 297 357 0.671 0.787 0.78 0.461
Epoch gpu_mem box obj cls labels img_size
11/49 13G 0.02719 0.005132 0 227 416: 100% 25/25 [00:32<00:00, 1.30s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.51s/it]
all 297 357 0.847 0.666 0.8 0.463
Epoch gpu_mem box obj cls labels img_size
12/49 13G 0.02633 0.004897 0 265 416: 100% 25/25 [00:32<00:00, 1.32s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.48s/it]
all 297 357 0.722 0.773 0.811 0.495
Epoch gpu_mem box obj cls labels img_size
13/49 13G 0.02559 0.005043 0 196 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.41s/it]
all 297 357 0.691 0.814 0.791 0.469
Epoch gpu_mem box obj cls labels img_size
14/49 13G 0.02537 0.004815 0 232 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.44s/it]
all 297 357 0.791 0.731 0.811 0.499
Epoch gpu_mem box obj cls labels img_size
15/49 13G 0.02512 0.004849 0 230 416: 100% 25/25 [00:34<00:00, 1.37s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.45s/it]
all 297 357 0.765 0.739 0.81 0.483
Epoch gpu_mem box obj cls labels img_size
16/49 13G 0.02504 0.004759 0 206 416: 100% 25/25 [00:33<00:00, 1.33s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.47s/it]
all 297 357 0.737 0.779 0.82 0.512
Epoch gpu_mem box obj cls labels img_size
17/49 13G 0.02469 0.004673 0 267 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.41s/it]
all 297 357 0.802 0.72 0.822 0.512
Epoch gpu_mem box obj cls labels img_size
18/49 13G 0.02447 0.004662 0 231 416: 100% 25/25 [00:33<00:00, 1.35s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.46s/it]
all 297 357 0.778 0.759 0.824 0.522
Epoch gpu_mem box obj cls labels img_size
19/49 13G 0.02424 0.004754 0 235 416: 100% 25/25 [00:33<00:00, 1.35s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.39s/it]
all 297 357 0.785 0.759 0.827 0.533
Epoch gpu_mem box obj cls labels img_size
20/49 13G 0.02374 0.004643 0 213 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.42s/it]
all 297 357 0.857 0.695 0.823 0.517
Epoch gpu_mem box obj cls labels img_size
21/49 13G 0.02402 0.004533 0 209 416: 100% 25/25 [00:34<00:00, 1.37s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.46s/it]
all 297 357 0.796 0.754 0.816 0.523
Epoch gpu_mem box obj cls labels img_size
22/49 13.6G 0.0235 0.004528 0 236 416: 100% 25/25 [00:32<00:00, 1.31s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.40s/it]
all 297 357 0.777 0.782 0.833 0.545
Epoch gpu_mem box obj cls labels img_size
23/49 13.6G 0.02366 0.004616 0 264 416: 100% 25/25 [00:33<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.44s/it]
all 297 357 0.816 0.748 0.832 0.531
Epoch gpu_mem box obj cls labels img_size
24/49 13.6G 0.02322 0.004491 0 238 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.49s/it]
all 297 357 0.814 0.748 0.829 0.519
Epoch gpu_mem box obj cls labels img_size
25/49 13.6G 0.02305 0.004363 0 213 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.40s/it]
all 297 357 0.768 0.773 0.835 0.536
Epoch gpu_mem box obj cls labels img_size
26/49 13.6G 0.02326 0.004525 0 238 416: 100% 25/25 [00:33<00:00, 1.33s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.43s/it]
all 297 357 0.801 0.787 0.849 0.552
Epoch gpu_mem box obj cls labels img_size
27/49 13.6G 0.02263 0.004288 0 250 416: 100% 25/25 [00:33<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.38s/it]
all 297 357 0.813 0.77 0.845 0.548
Epoch gpu_mem box obj cls labels img_size
28/49 13.6G 0.02294 0.004502 0 245 416: 100% 25/25 [00:33<00:00, 1.33s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.46s/it]
all 297 357 0.821 0.762 0.84 0.546
Epoch gpu_mem box obj cls labels img_size
29/49 13.6G 0.02249 0.004358 0 223 416: 100% 25/25 [00:33<00:00, 1.35s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.42s/it]
all 297 357 0.811 0.78 0.839 0.547
Epoch gpu_mem box obj cls labels img_size
30/49 13.7G 0.0226 0.004365 0 234 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.40s/it]
all 297 357 0.832 0.75 0.837 0.545
Epoch gpu_mem box obj cls labels img_size
31/49 13.7G 0.02216 0.004202 0 218 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.39s/it]
all 297 357 0.847 0.744 0.841 0.542
Epoch gpu_mem box obj cls labels img_size
32/49 13.7G 0.02241 0.004421 0 258 416: 100% 25/25 [00:33<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.45s/it]
all 297 357 0.789 0.798 0.841 0.553
Epoch gpu_mem box obj cls labels img_size
33/49 13.7G 0.02187 0.004324 0 183 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.42s/it]
all 297 357 0.798 0.798 0.847 0.551
Epoch gpu_mem box obj cls labels img_size
34/49 13.7G 0.02235 0.004243 0 217 416: 100% 25/25 [00:32<00:00, 1.30s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.45s/it]
all 297 357 0.821 0.773 0.843 0.55
Epoch gpu_mem box obj cls labels img_size
35/49 13.7G 0.02182 0.004277 0 234 416: 100% 25/25 [00:33<00:00, 1.35s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.42s/it]
all 297 357 0.804 0.796 0.849 0.559
Epoch gpu_mem box obj cls labels img_size
36/49 13.7G 0.02203 0.004312 0 260 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.47s/it]
all 297 357 0.809 0.784 0.846 0.553
Epoch gpu_mem box obj cls labels img_size
37/49 13.7G 0.02222 0.00428 0 200 416: 100% 25/25 [00:32<00:00, 1.31s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.43s/it]
all 297 357 0.806 0.804 0.85 0.557
Epoch gpu_mem box obj cls labels img_size
38/49 13.7G 0.02202 0.004223 0 210 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.46s/it]
all 297 357 0.784 0.796 0.836 0.551
Epoch gpu_mem box obj cls labels img_size
39/49 13.7G 0.02193 0.004199 0 256 416: 100% 25/25 [00:34<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.43s/it]
all 297 357 0.804 0.795 0.844 0.556
Epoch gpu_mem box obj cls labels img_size
40/49 13.7G 0.02192 0.004291 0 246 416: 100% 25/25 [00:34<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.24s/it]
all 297 357 0.792 0.8 0.839 0.558
Epoch gpu_mem box obj cls labels img_size
41/49 13.7G 0.02164 0.004269 0 235 416: 100% 25/25 [00:32<00:00, 1.31s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.47s/it]
all 297 357 0.783 0.81 0.842 0.561
Epoch gpu_mem box obj cls labels img_size
42/49 13.7G 0.02207 0.004228 0 247 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.43s/it]
all 297 357 0.79 0.812 0.845 0.562
Epoch gpu_mem box obj cls labels img_size
43/49 13.7G 0.02193 0.004293 0 263 416: 100% 25/25 [00:33<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.57s/it]
all 297 357 0.796 0.801 0.85 0.561
Epoch gpu_mem box obj cls labels img_size
44/49 13.7G 0.02202 0.004254 0 242 416: 100% 25/25 [00:34<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.44s/it]
all 297 357 0.81 0.793 0.849 0.556
Epoch gpu_mem box obj cls labels img_size
45/49 13.7G 0.02163 0.004189 0 209 416: 100% 25/25 [00:33<00:00, 1.33s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.48s/it]
all 297 357 0.791 0.807 0.849 0.557
Epoch gpu_mem box obj cls labels img_size
46/49 13.7G 0.02168 0.004311 0 241 416: 100% 25/25 [00:34<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.44s/it]
all 297 357 0.801 0.801 0.844 0.556
Epoch gpu_mem box obj cls labels img_size
47/49 13.7G 0.02202 0.004218 0 231 416: 100% 25/25 [00:33<00:00, 1.36s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.44s/it]
all 297 357 0.811 0.793 0.847 0.559
Epoch gpu_mem box obj cls labels img_size
48/49 13.7G 0.02156 0.004261 0 230 416: 100% 25/25 [00:32<00:00, 1.32s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.51s/it]
all 297 357 0.835 0.765 0.842 0.556
Epoch gpu_mem box obj cls labels img_size
49/49 13.7G 0.02169 0.004359 0 239 416: 100% 25/25 [00:33<00:00, 1.34s/it]
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:02<00:00, 1.43s/it]
all 297 357 0.803 0.81 0.851 0.561
51 epochs completed in 0.526 hours.
Optimizer stripped from yolov5_runs/train/exp2/weights/last.pt, 14.4MB
Optimizer stripped from yolov5_runs/train/exp2/weights/best.pt, 14.4MB
Validating yolov5_runs/train/exp2/weights/best.pt...
Fusing layers...
YOLOv5s summary: 224 layers, 7053910 parameters, 0 gradients, 16.3 GFLOPs
Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 2/2 [00:03<00:00, 1.97s/it]
all 297 357 0.789 0.815 0.845 0.562
Results saved to yolov5_runs/train/exp2